dc.creatorDe La Vega, Gerardo, José
dc.creatorCorley, Juan Carlos
dc.date.accessioned2020-07-17T16:34:16Z
dc.date.accessioned2023-03-15T14:05:02Z
dc.date.available2020-07-17T16:34:16Z
dc.date.available2023-03-15T14:05:02Z
dc.date.created2020-07-17T16:34:16Z
dc.date.issued2019
dc.identifier1366-5863
dc.identifierhttps://doi.org/10.1080/09670874.2018.1547460
dc.identifierhttp://hdl.handle.net/20.500.12123/7571
dc.identifierhttps://www.tandfonline.com/doi/abs/10.1080/09670874.2018.1547460
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/6210660
dc.description.abstractSpatial distributions models (SDM) are often used in invasive pest management to understand current and potential distribution. Using data on the well-studied spotted wing drosophila as a model, we compared distribution patterns of the range-limit with commonly applied correlative and mechanistic models. Correlative models risk underestimation whereas simple mechanistic models provide overestimated range predictions, although using both approaches for the spotted wing drosophila improved range-limit predictions. Model choice when dealing with pests is central to the accurate identification of invasive species limit range and consequently for the deployment of monitoring and early detection programs.
dc.languageeng
dc.publisherTaylor & Francis
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceInternational Journal of Pest Management 65 (3) : 217-227 (2019)
dc.subjectInsecta
dc.subjectDrosophila
dc.subjectEspecie Invasiva
dc.subjectInvasive Species
dc.titleDrosophila suzukii (Diptera: Drosophilidae) distribution modelling improves our understanding of pest range limits
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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